کیخسرو یاکیده

Nowadays, knowledge-based governance can have a valuable impact on improving the performance of both government and private institutions. However, there is a possibility of overlooking the influential factors on this type of governance. Therefore, adherence to the principles of knowledge-based governance can contribute to improving the situation of organizations, and society, allowing for the maximum utilization of individuals' abilities, reducing societal challenges, and ultimately pursuing the public welfare. This research has employed a qualitative methodology and is based on Grounded theory, using the approaches of Strauss and Corbin. The study population consists of experts familiar with the subject, with 12 of them being selected through purposive and snowball sampling methods for in-depth interviews. We used MAXQDA software to analyse the data. 302 codes are identified and placed in the 46 subcategories and 18 main categories, which are in 6 main categories under the headings of causal conditions, including sharing, creating, preserving and maintaining knowledge, competence of managers. background conditions, including creating infrastructure, structure organization and culture of the organization. Intermediate conditions include rules and procedures, performance evaluation, transparency, team building, recruitment and retention, planning and administration system. The innovation dynamic capability and development strategy are strategic conditions. The performance of the society, organization and the employees are the consequence. The central condition is knowledge-based governance. The Grounded approach and model design in executive organizations has a unique aspect and facilitate the implementation of knowledge governance in executive organizations of the country.

There are different patterns to measure the performance of competitiveness of tourist destinations. One of the most common is the one provided by World Economic Forum.  Tourism competitiveness index is measured based on four main components and 14 pillars, including Environmental Empowerment (Business Environment, Security and Safety, Health and Hygiene, Human Resources and Labor Market, ICT Readiness,) Policies (Prioritizsation of Travel and Tourism, International Openness, Price Competitiveness and Environmental Sustanability), Infrastructures (Air Transport Infrastructure, Ground an Port Infrastructure and Tourist Service Infrastructure) and Resources (Natural Resources, Cultural Resources and Bussines Travel)The ranking method applying by the World Economic Forum is  just simple averaging indicators  without  any weights, so by weighing the indicators, the pattern  can be improved. The aim of this study was to rerank countries applying multi-criteria decision-making methods where allocating weights to indicators are common. this research is an applied research in terms of objective while because of using a questionnaire for data collection, could be categorized as a survey research. To measure the importance of items, the opinions of eight knowledgeable experts in the field of tourism were gathered via the standard questionnaire and eventually the importance of each items was determined through GAMZ software. Finally, 14 criteria and 87 sub-criteria were ranked. The most important criteria order are tourism, Health and Hygiene, Air Transport Infrastructure, Security and Safety, International Openness, Tourist Service Infrastructure, Environmental Sustainability, Human Resources and Labor Market, ICT Readiness, Business Environment, Price Competitiveness, Natural Resources, Ground and Port Infrastructure and Cultural Resources and Bussines Travel.

The purpose of this study is evaluating efficiency of the teams participating in 2016 Colombia Futsal World Cup.

This study is of descriptive type and desk research in terms of data collection. The statistical population and sample consist of all the teams participating in 2016 Futsal World Cup in Columbia. The data was collected from the website of the Federation International de Football Association (FIFA). DEA-BCC model was used in order to analyze the data and determine the efficiency of the teams in terms of both offensive and defensive power.

The results showed that in terms of offensive power, Brazil, Russia and Paraguay, and in terms of defensive power, Ukraine and Portugal were the most efficient teams in this tournament. The overall efficiency results showed that Brazil had a better performance compared to the other teams. Finally, the results of hypotheses testing showed that the top 12 teams in this tournament were more efficient in all three cases of offensive, defensive, and overall performance compared to the bottom 12 teams.

Recognizing their offensive and defensive powers, teams can prepare themselves for the future events through smarter planning and more effective trainings

In Workplaces, organizations need to balance warehouse inventory and maintenance costs. Therefore, inventory control is one of the major concerns of organizations. In many organizations, they use the ABC classification method for controlling a large volume of inventory. in the traditional ABC classification, items are categorized only by a single criterion; but considering other criteria is also essential, so in such cases, the multi-criteria inventory classification is used. The purpose of this study is to present a new model in multi-criteria inventory classification.

In this study, the data envelopment analysis method has been used to present an appropriate model for inventory classification. In the literature of Radial and non-radial models of data envelopment analysis have been used in inventory classification and the comparison of the results of the models indicates that non-radial models provide a more rational classification. Hence, other types of non-radial models have been proposed in this paper to improve inventory classification.

the proposed method does not have the weakness of the radial models and improves the multi-criteria inventory classification using non-radial models.

47 items of inventory related to a common numerical example in the literature as well as 80 items of inventory items of Pars Khazar industrial company have been used in order To implement the new models and compare them with existing models. The results of comparing the proposed model with the existing ones in the literature show the superiority of the proposed model.

The imposed policies in countries, irrespective of the present dynamic domestic environment and global markets and the main players of the export environments in the field of production and export of industrial goods has caused reduction of the export performance of companies and questioned their effectiveness. Moreover, the inability to identify the main factors affecting the export performance of countries among the small and medium enterprises, lack of enough attention to the local characteristics of countries and the lack of proper management of the interaction environment lead to the impairment and weakness of export performance. Shortage of abstract maps or conceptual models to explore the most important influencing factors on exports, and the structural and dynamic communication between them is observed in governmental and academic export institutions. And it will have a negative impact on corporate export performance. Therefore, from a theoretical point of view, lack of a structure for management of the export ecosystem in the form of a macro system can have a negative impact on the export performance of countries and companies. Accordingly, the main focus of the present research is on the theoretical and practical gaps in the field of export performance and low focus on the management of dynamic interactions between the influential players in export performance. Therefore, it is necessary to examine and analyze the interactive relationship between these players in order to create a suitable platform for effective management of the export performance in companies. Hence, the aim of this study is to investigate the factors, at the company level, that affect the export of industrial goods in small and medium companies (regardless of the destination country and type of export market) as well as to analyze the relationship between these factors.

This study uses mixed-method (a combination of qualitative and quantitative data) and it is developmental in terms of purpose. In the first stage of the mixed-method research, the influential factors on the companies’ industrial performance which were extracted from the empirical background were clustered based on the qualitative approach and through Causal Cognitive Mapping method using Ucinet software. Accordingly, through judgmental sampling, in-depth interviews were conducted with 11 experts in the Iranian Chamber of Commerce and the Ministry of Industry, Mines and Trade. 

In this study, 4 clusters were identified regarding the industrial export ecosystem at the company level. These four clusters include knowledge hegemonic, production culture, market diplomacy and enterprise’ human structure. Cognitive hegemony cluster contains a) analysis of foreign competitors, b) analysis of political and economic stability in the destination country, c) commitment to implementation of marketing strategies, and d) raising awareness about the foreign market culture. Production culture cluster encompasses a) commitment to quality, b) learning-centeredness, c) commitment to apply up-to-date technology, and d) flexibility of production process. Market diplomacy cluster includes a) international image of enterprise managers, b) familiarity with the laws of the destination country, c) strategic alliance with the competitors, and d) appropriate communication with foreign distributors. And finally enterprise’s human structure cluster includes a) managers’ professional skills, b) employee’s knowledge and experience, and c) recruiting youngsters at management levels.  

Two main and fundamental findings were obtained in this study. The first finding refers to the clustering of the effective factors on the export performance of companies based on their homogeneity and correlation (as well as confirming the effectiveness of these clusters on the export performance of companies based on statistical analysis), and the second finding refers to examining the relationship between these clusters and sensitivity analysis of causal relationship. Regarding the first finding, it is believed that the industrial export ecosystem at the company level encompasses four clusters of knowledge hegemony, production culture, production diplomacy and enterprise’ human structure. Each factor affects the enterprise’ environment from a unique perspective and if the relations are properly regulated, one can witness the growth of industrial performance among enterprises.

The aim of this study is to design an industrial goods export ecosystem for SMEs, so that they can play a full role in the country's economic growth. Based on research literature, 15 actors influencing the export performance of industrial firms were identified and their relationship was analyzed by eleven experts from the Ministry of Industry, Mine and Trade, and the Iranian Chamber of Commerce, who were selected by judgmental sampling. Interviews have been analyzed through a causal cognitive mapping method and by Ucinet and Netdraw software. The actors influencing the export performance of the private sector in SMEs were classified into four clusters: Knowledge Hegemony, Culture of Product, Market Diplomacy, and human Structure of the Firm. The first three clusters have a strong and mutually interactive interaction, and the cluster of Human Structure of the Firm is also effective as an infrastructure element on Knowledge Hegemony and Cultures of Product. Enterprises should focus on all four of these clusters to achieve high export performance and design and implement unique strategies for each of them. Failure to pay attention to each of these four clusters will reduce the export performance of companies. Market Diplomacy, and Culture of Product are innovative concepts that companies need to learn in these areas for high export performance.

The aim of this study is Evaluating Efficiency of the Teams Basketball that Presence in Olympic 2016 Brazil. The study is descriptive-analytical in terms of data collection is attributive and libraries. The statistical population consisted of all teams participating in the Men's Olympic Basketball in Brazil (2016).  Because of limitation in amount of population, the sample size was considered equal to the population size (N=12). The data refer to the site of the World Federation of Association basketball (FIBA) and classified in two offensive and defensive phases and for analyzed with using SPSS19 and DEA software. The results showed that two teams in offensive phase include Nigeria and USA has full efficiency were equal to 1. Croatia, France, Lithuania, Argentina and Nigeria also the most efficient teams as well as teams in the tournament were the defensive phase. Also, there was no relationship between ranked teams’ performance and position. As a result, the coaches of the basketball team of Iran and other countries can recognize the opponents' offensive and defensive status by choosing more effective plans and exercises and choosing a more appropriate strategy to confront their rivals and reduce their distance with the titular countries.

Nowadays Corporate Social Responsibility (CSR) seems to be mandatory for organizations to gain environmental legitimacy and to keep maintaining environmental sustainability as well. CSR has a positive effect on organization credibility, and, it can be considered too as the competitive advantage for any firm. for analyzing the impact of competitive strategies on both environment commitment and social engagement dimensions of CSR, it's estimated 381 the minimum size of sample, by cohen's d formula. Finally it's distributed among 450 big and reputable Iranian manufacturing and service corporations in 2015 extracted from IMI, and Gathered data of 393 Iranian manufacturing and service corporations has been analyzed by AMOS. Results indicate that differentiation strategy has the positive impact on social engagement and environmental commitments, yet, cost leadership strategy has the positive effects only on social engagement. Also, the legal nature of the organization which is indicative of establishing firms as governmental or private moderate correlations between differentiation strategies and mentioned distinguished dimensions of CSR. This shows that meaningful differences appear between CSR(s) in Iranian private and governmental firms when they arrange for differentiation strategies.

 

Organizations in addition to creating and delivering value to their customers, so that while they satisfy their customers, they can also make profit from it. Many researches have been conducted about predicting the customer value and in some of them, the customer lifespan and the customer value have been discussed, though the combination of these two is a new work. The main purpose of this research is to investigate the connection of customer value, satisfaction, loyalty and valuation and finally the organization position in competition market. In this research, the civil companies were chosen in the second half of 2015 , it was studied based on purposeful subjects. Then, after studying research literature and interviewing with 6 individuals of professors and experts, an existing model of customer value generation extracted from a research conducted in 2010 were used and two variables were added to this model and 7 hypotheses were tested. After the distribution of the conducted questionnaires among 130 civil companies in Iran and gathering 70 filled questionnaires and analyzing the structural equations of basic variance through PLS software, it was indicated that the capability and coolness have a deep impact on predicting the costumer value. Customer value generation and customer satisfaction also have an enormous impact on customer loyalty. Finally, customer value generation and loyalty effect the organization position in competition market as two separate factors.

Decision making units (DMUs) with network structure can be operated into series subsystems where each subsystem in the series may consist of parallel divisions or may not. In this case, the system eciency shows the performance of the system, series subsystems, and parallel divisions. The mixed structure network DEA models are developed into deterministic linear programming models under the assumption of constant return to scale (CRS) with undesirable outputs. In this study, the performance of the supply chain of Iran's power industry has been evaluated in a series- parallel structure. The supply chain includes the sixteen regions of generation, transmission, and distribution subsystems, which are interconnected in series format. Power plants and power distribution companies are also considered in the calculation of eciency scores with a parallel and independent divisions. The main contribution of the paper are 1) to develop the constraints for evaluating parallel divisions using a constant lambda coecient in a network-slack based measure models; 2) to determine the origin of ine ciency in generation, transmission, and distribution subsystems, power plants, and distribution companies; 3) to consider the all types of inputs, intermediate measures, the desired and undesired intermediate and nal outputs; and 4) to consider the real case study at the level of the Iranian power industry. The Network DEA Models of the paper is to evaluate the performance of the system and multi subsystems which are formed of unequal and parallel divisions. The proposed models provide the origin of the ineciency for system and subsystems. Also, the ndings shown that the eciency percentage of ecient DMUs for the system, generation, transmission, and distribution subsystems are respectively 12.5, 31.25, 31.25, 25.

Banks are considered as vital circulatory system of finance and financial institutions that collect assets from various sources and allocate them to sectors that need market liquidity. Despite existing limitations, the present enquiry aimed to examine the efficiency of bank management through the use of Data Envelopment Analysis Model. Typical Models of Data Envelopment Analysis employed in evaluation of organizational performance are based on the black box events, that is, the input into units under scrutiny converted into output regardless of the intermediate stages. However, providing bank services is a complex process comprising different interconnected stages and the interwoven stages involved necessitated the use of Network Data Envelopment Analysis, in the present study, to design a Bank Performance Measurement Model. Thus, the aim of this scrutiny was to identify managerial weaknesses by calculating the management efficiency using the Network Model and to offer viable solutions. To serve the purpose, the banking data accumulated in 19 private bank branches in Tehran during the year 2014 were surveyed to estimate both the overall efficiency and the efficiency of each bank segment. The findings indicated significantly lower levels of efficiency in Network Collective Models compared to Simple Collective Models. Also, the NSBM model rendered a more precise measure of efficiency in comparison to the SBM model which can enable managers to identify and rectify inefficiencies in each sector.

Tobin index is one of the most important indices in the world of investment used as a criterion for evaluating performance of the firms to decide for the right investments. However, there are some ambiguities in the accuracy of the results based on this index that have prompted researchers to pursue estimation of this index based on the other financial indices. But Tobin index is a dynamic index and as it is based on the market price, may be changed its value at once, therefore it is not logical to be predicted using methods as multiple regression that attempt to predict precise value of depent variable. this research has reviewed methods based on the exact prediction like regression to judge about Tobin index by the other financial indices and it has recommended using discriminant analysis methods such as logistic regression and artificial nervous network. Discriminant analysis is a method to categorize a set of the observations into one of two or several determined groups, so that observations within each group can have the most similarity to each other. Therefore, this research has analyzed Tobin index discrimination using financial information of 184 accepted firms by Tehran Stock Exchange in the financial year leading to 29 of Esfand in 1393 by logistic regression and artificial nervous network and it has reported results of two techniques and has compared output of the two techniques to each other.

Paying attention to the growth of organizations, in line with sustainable development of the countries, has always been one of the policies of the managers of all organizations among which are banks. An examination of the desirable trend of a bank can only be done by measuring its performance based on standard criteria, comparing that bank with other banks and, finally, ranking them among the banks. In this research, the model of efficiency calculation in data envelopment analysis was used to rank the banks of the country based on CAMEL standard indices. Among the data envelopment analysis models, the modified domain model (RAM) is capable of considering both inputs and outputs simultaneously, presenting a numerical index for efficiency and accepting negative input and output. Thus, the RAM model has been used as the basis for ranking banks in this research. In order to examine and evaluate the performance of the banks, the financial ratios extracted from the financial statements of banks were used. These ratios were obtained to cover five characteristics of CAMEL, namely, capital adequacy, asset quality, management, profitability and liquidity. According to the results of the research, five banks, Karafarin, Dey, Sina and Pasargad banks, were the most efficient among the 12 selected banks.

Many organizations use the ABC classification method to control their large amount of inventories. The most common way to classify inventories is the ABC method. In traditional ABC classification, items are only classified according to one criteria. But there are other criteria that need to be considered in the inventory classification. The purpose of this study is to present a new model for multi-criteria inventory classification. Among the multi-criteria inventory classification methods, DEA-based methods do not require decision makers to determine the weight of the criteria; however, in the literature, only the radial methods of data envelopment analysis are used to classify inventory items. In this paper, the cross-efficiency of a non-radial model is proposed in order to improve the average cross-efficiency of the R model, which is a radial model. Therefore, the proposed method does not have the weakness of R model due to the use of a non-radial model and also it has benefits the cross-efficiency method. The models were executed on 47 items of inventory related to a common numerical example in the research literature as well as on 80 items of inventory of the Pars Khazar Industrial Company and the results of the implementation of the models have been analyzed. The results of comparing the proposed model with some of the existing models in the literature indicate the superiority of the proposed model.

Organizational ambidexterity refers to an organization’s capacity to pursue two distinct goals at the same time, and is known as an important criterion in achieving competitive advantage. So far, many studies have been documented on the concept of organizational ambidexterityand its impact on performance. Nevertheless, few studies have examined its dual dimensions. Evidences suggest that ambidexterity has been positively correlated with performance, and for an organization, it is a valuable tool for continuously improvement in the performance. In this study, ambidexterity has been considered as a construct with two dimensions of balance and combination, and attempt has been made to measure the relationship between this two dimensions and the performance in banking industry. To do so, initially, reviewing the literature, the conceptual model of this study was extracted, and then in order to analyze the research model and hypotheses, we examined 161 bank branches. The structural equation modeling based on partial least squares (PLS) was used to analyze the data. The data analysis suggested a significantly positive impact of ambidexterity on performance which means if the organizations achieve high level of exploitation and exploration, the performance will improve. In this study, the increase in the combined amount of two exploitation and exploration activities or on the absolute value of the difference between these two activities was pointed out and according to the two aforementioned viewpoints, the role of ambidexterity on the performance was investigated. The contradictory results of the research in the two balanced and combined approaches indicated that it is not the balance between the two dimensions of exploitation and exploration that has a positive effect on performance and any increase in each of these two dimensions can lead to the improvement of the performance.

Today, in both developed and developing countries, there has been increasing attention to investment in small- and medium-sized enterprises (SMEs). Due to their flexibility and dynamism structure, SMEs could easily adapt themselves to the demands of customers, who have changed their styles rather than the past and seek various products and enter into the market of different countries. On the other hand, because SME's make a large share of employment and products in developed and developing countries, policies have pushed toward greater support and activation of this sector. According to this, the present study is aimed at investigating the empowerment of SMEs. This research enjoys the use of an applied and analytical method. In order to identify the factors, documents of 7 organizations under the Ministry of Industry, Mine and Trade of Iran (Small Industries and Industrial Parks Organization, Trade Promotion Organization of Iran, Investment Guarantee Fund, Export Guarantee Fund of Iran, Industrial Development and Renovation organization of Iran, Bank of Industry & Mine and Consumers and Producers Protection Organization) were reviewed, and semi-structured interviews of experts were used through qualitative thematic analysis. The results of content analysis and interview with experts were classified into six main criteria (including financial and credit support, trade support, infrastructure support, information and knowledge support, facilitating rules and social and cultural support) and led to 31 subcriteria.

Investing in the stock market has always been a key issue that how liquid assets are specialized among stocks of the companies to meet the interests of the investor. This research is tried to help investors to choose portfolio optimization more effectively by offering two new approaches .The approach of using cross-efficiency table instead of stock return is presented as the basis to solve the model of the minimum mean of absolute deviations from the average, in which financial indicators were used as initial data to form the portfolio. Another approach is a two-stage algorithm in which the requirement for segmentation of the market to various industries has been considered when using financial indicators. Finally, sharp criteria shows that there is a significant difference between the proposed approaches and the current methods. The results show that these two approaches are more suitable than similar ones.

The aim of this study is to propose a new method for portfolio optimization based on financial ratios. In this method, cross efficiency scores are produced from financial ratios, using Data Envelopment Analysis. Mathematical interpretation of these cross efficiency scores that allocates several score to each company is efficiency of company in probably future situations. Efficiency scores calculated based on proper financial ratios can be considered as financial strength. Thus cross efficiency scores produced from financial ratios, can be considered as potential financial strength. As future is not clear, potential financial strength can be presented in expectation and risk indices that are mean and variance of cross efficiencies. Fraction of expectation to risk for potential financial strengths can be used as a criterion for pairwise comparison of companies. Eigenvector associated with the biggest eigenvalue of pairwise comparison matrix reflects relative importance weights of companies. This paper proposes relative importance weights of companies as a basis for portfolio optimization. Based on sharp index Performance of proposed method is acceptable and better than marker portfolio and portfolio of one similar method.

Markowitz model is the base for modern approach to portfolio optimization problem. Markowitz model is formulated based on mean and variance of portfolio that is calculated based of historical return. Since this model was proposed many effort have been done to improve formulation of portfolio optimization problem. One of the most important improvement is substituting variance by downside risk measure. Downside risk measure account for fluctuation that just occurs below the mean of returns .The other improvement that recently proposed is data generation based on data envelopment analysis (DEA) and using generated data instead of historical returns. This new improvement that essentially changed basis of portfolio optimization problem provide an opportunity for researcher to examine kinds risk measure based on generated data instead of historical return.In this paper data envelopment analysis is used for generating cross efficiencies based on financial ratios. Then Value at Risk (VaR) as a downside risk measure is redefined for using on cross efficiencies. A well known linear model is used for determining weighs of portfolio based on minimization of Value at Risk. Performance method is evaluated by applying on 185 stock from Tehran Stock Exchange and comparing Sharp criteria proposed portfolios, market portfolio and application of Markowitz model on cross efficiencies during 2011 to 2015. Sharp criteria reveals that proposed method has better performance than the other methods.

In this paper, the pattern of efficiency calculation with data envelopment analysis (DEA) is used to present a consolidated index for representing different dimensions of stock liquidity. Among DEA models, the range adjusted model (RAM) considers both inputs and outputs simultaneously; provide measure of efficiency and deals with negative inputs and outputs. Thus in this paper, RAM model is used as a basis for presenting relative consolidated index of liquidity. The next step, units with relative consolidated index equal to one is ranked, based on the full-inefficient frontier ranking method. Results support the effectiveness of data envelopment analysis application for measuring liquidity relative consolidated. Using this method, the stock liquidity consolidated index allocated to each of the companies listed on the, presents different aspects of stock liquidity for stocks in stock exchange, in a way that liquidity of stocks can be compared with each other easily and liquidity of a specific stock can be surveyed during time prides.

The aim of this study is to evaluate efficiency of the power industry using an integrated approach of Network DEA with a variety of outputs and Windows Analysis. This network system includes undesirable, final desirable and intermediate output in time interval of 2012 to 2014. Input and output variables of first and second stages were respectively considered as domestic consumption of power stations, fuel consumption, thermal output, efficiency, nominal power of power station and operational power of power station, maximum production, especial production and gross production, capacity of power transmission substations, and finally delivery energy and energy losses. The results indicate that due to the possibility of integration over three times, in terms of total efficiency and efficiency of production stage, there is highest number of efficient units. In 2013 However, compared to efficient frontier of three periods, electricity production stage had the greatest number of inefficient units and increasing the number of efficient units in the total efficiency stage is due to high efficiency of regional electricity companies.

Portfolio optimization problem is one of the most important investment problems. Most of the mathematical models, presented for solving this problem are based on historical returns of stocks. Utilizing cross efficiencies, calculated by data envelopment analysis models, instead of historical returns, has attracted considerations just recently. In this paper table of cross efficiencies that is a collection of indicators about future possible state of each corporation, is considered as a return matrix of a zero- sum game between the investor and the market. It is assumed in this double game that the Investors can choose the corporation to invest and market can turn the conditions in favor of each of the corporations. Assuming a zero-sum reflects a confrontation between investors and the market which is right for spirit of caution against market. Optimal portfolio determines by the optimum possibilities that is achieved through solving the game in favor of the investor. Results show that the Performance of proposed method is acceptable in compare with market portfolio.

Markowitz model is the first modern formulation of portfolio optimization problem. Relying on historical return of stocks as basic information and using variance as a risk measure are tow drawbacks of this model. Since Markowitz model has been presented, many efforts have been done to remove theses drawbacks. On one hand several better risk measures have been introduced and proper models have been developed to detect optimized portfolio based on them. On the other hand the idea of using generated data by data envelopment analysis instead of historical return of stocks has been presented. In this paper, both improvements are collected by applying a conditional value at risk minimization linear model on cross efficiencies, generated by a proper model of data envelopment analysis model, called range adjusted model. Performance of proposed method, market portfolio as a benchmark and method of applying Markowitz model on cross efficiencies calculated according to sharp ratio using next year real return of each portfolio during years of study. Results support proper performance of proposed method.

Ambidexterity concept refers to the ability of organizations to address two incompatible objectives. In environmental uncertainty, organizational ambidexterity typically has a positive effect on performance and leads to sustainable competitive advantage, long-term success and survival. Nevertheless, it is possible only when the culture enables organizational members to exploit current competence (exploitation) and explore new opportunities and abilities (exploration).The purpose of this study is to assess the effects of organizational culture ambidexterity and organizational ambidexterity on performance. In order to evaluate the research hypotheses, companies operating in the food industry were selected as population and questionnaires from managers of 62 companies is collected and analyzed. The proposed model is analyzed using Structural Equation Modeling techniques with the help of Warp PLS program. Results support the relationship between organizational culture ambidexterity and organizational ambidexterity, as well as their relationship with performance. Also according to the results, organizational ambidexterity has a mediator role in the relationship between organizational culture ambidexterity and performance.